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3rd international Workshop on New Approaches for Multidimensional Signal Processing, NAMSP 2022

3rd International Workshop on New Approaches for Multidimens...

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3rd international Workshop on New Approaches for Multidimensional Signal Processing, NAMSP 2022

ISBN: (纸本)9789811978418

The proceedings contain 23 papers. The special focus in this conference is on New Approaches for Multidimensional Signal Processing. The topics include: Development of IoT Indoor Monitoring System for Independent Elderly;improving the Process of Evaluating User Stories Using the Paraconsistent Annotated Evidential Logic Eτ;neural Network Algorithm Applied in Electrical Engineering Automation;Truss Structure Optimization Design Based on FE-PSO-SQP Algorithm;practice System of Ant Colony Optimization Algorithm in Business Administration;literature Review of Smart Contracts Using Blockchain Technology;a Comprehensive Study of 5th Generation Scheduling Algorithms;a Comparative Analysis of Homogeneous and Heterogeneous Protocols to Maximize the Lifetime of Wireless Sensor Network for Precision Agriculture;the Integration Development and Upgrading Path of Industry 4.0 Architecture Industrial Engineering Network Driven by Big Data;video Tracing of Moving Objects by Fusing Three-Term Decompositions;SAAS Application Prospect Analysis in Hrm and Methods to Upgrade the Contemporary System;All Digital Phase Locked Loop (ADPLL) and Its Blocks—A Comprehensive Knowledge;on Realization of Smart Logistic Warehouse Management with Internet of Things;development and Design of Intelligent Traction System for Bulk Cargo Terminal;deep Learning Approaches for Classroom Audio Classification Using Mel Spectrograms;Tensor Spectral Pyramid for Color Video Sequences Representation, Based on 3D FO-AHKLT;electromyography Signal Acquisition, Processing, Optimization and Its Applications;research on the Radar Signal Classification Method Based on the Deep Faith Network Model;measuring machine intelligence Using Black-Box-Based Universal intelligence Metrics;COVID Detection Using ECG Image Reports: A Survey;disease Detection Techniques in Plants: Transition from Manual to Automation.

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Algorithm for Fault Diagnosis System of Pumping Units Based on Fuzzy Logic and Neural Networks

Algorithm for Fault Diagnosis System of Pumping Units Based ...

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Artificial intelligence and Autonomous Robot Systems (AIARS), international conference on

作者： Guannan Zhang No.4 Operation Area of No.6 Oil Production Plant of Daqing Oilfield Co. Ltd Daqing Heilongjiang China

ISBN: (数字)9798350376173

ISBN: (纸本)9798350376180

In order to reduce the exploitation cost, improve the economic benefit and ensure the sustainable exploitation of crude oil, it is particularly urgent to innovate the oil extraction technology. This paper introduces two advanced intelligent technologies, fuzzy logic and neural network. Fuzzy logic can deal with uncertain and fuzzy information, which provides an effective means to deal with the complex faults of pumping units. Neural network, through its powerful self-learning and pattern recognition ability, provides a high-accuracy solution for fault classification and recognition of pumping units. Through experimental verification, this paper finds that the fault diagnosis method of pumping unit based on fuzzy logic and neural network is significantly better than the traditional method in accuracy and efficiency. This method can not only identify fault types and causes more accurately, but also realize timely early warning and prediction of faults, thus greatly improving the safety and production efficiency of oil fields. The fault diagnosis technology based on fuzzy logic and neural network provides strong support for the intelligent development of oil fields, and also lays a solid foundation for the intelligent, efficient and safe exploitation of oil fields in the future.

关键词： Fault diagnosis Fuzzy logic Accuracy Oils Neural networks Production Solids pattern recognition Safety Optimization

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A Tunnel Structural Health Monitoring and Damage Identification Algorithm Based on Deep Reinforcement Learning

A Tunnel Structural Health Monitoring and Damage Identificat...

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Artificial intelligence and Autonomous Robot Systems (AIARS), international conference on

作者： Yike Wei Bin Yang China Merchants Chongqing Testing Center for Highway Engineering CO. LTD Chongqing China

ISBN: (数字)9798350376173

ISBN: (纸本)9798350376180

With the continuous promotion of infrastructure construction such as water conservancy, transportation, and municipal engineering in China, the number of tunnels put into operation is increasing, making the healthy service and longterm operation of tunnel structures an urgent and important task. During tunnel operation, structural diseases such as cracks, voids, voids, and water seepage occur frequently. These diseases not only weaken the strength of the tunnel structure and shorten its service life, but also pose a serious threat to the safety of people's lives and property. This paper proposes a tunnel structure health monitoring and damage identification algorithm based on deep reinforcement learning (DRL) to address this issue. This algorithm fully utilizes the advantages of deep learning (DL) in feature extraction and pattern recognition, as well as the ability of reinforcement learning (RL) in decision optimization and adaptive learning. By constructing a model for the interaction between intelligent agents and the environment, it achieves real-time monitoring of the health status of tunnel structures and damage recognition. The experimental results show that the algorithm can accurately identify the damage situation of tunnel structures, effectively monitor the health status of tunnels, and provide strong technical support for the safe operation of tunnels.

关键词： Water conservation Feature extraction Deep reinforcement learning Real-time systems pattern recognition Intelligent agents Monitoring Optimization Testing Diseases

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Analysing the Need for 5G Networks based on Smartphone Market Penetration 3

Analysing the Need for 5G Networks based on Smartphone Marke...

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3rd international conference on Intelligent Communication and Computational Techniques, ICCT 2023

作者： Panse, Chetan Chaskar, Aayush Sibm Symbiosis International Deemed University Pune India

ISBN: (纸本)9781665453578

The term '5G' refers to the latest advancements in mobile technology. The next key stage of mobile communications standards after the soon-to-be-implemented 4G standards is 5G. Due to the development of 5G technology, the bulk of high bandwidth users will change how they access their phones. With 5G pushed via a VOIP-equipped smartphone, people would experience a volume of calls and data transfer unlike anything else. [1] The word '5G' relates to the generation of wireless telecommunications, which will change multiple areas of our daily life. Due to emerging mobile technologies like virtual reality applications, HD video consumption, and cloud-based entertainment, mobile users and their usage is expanding very quickly. The rate of increase in demand and the predicted trends of new technologies, such as driverless vehicles and virtual reality, will far exceed the capacity of 4G networks in a few years Consequently, multiple attempts have been made by industry experts and research associations to make 5G networks a reality soon. Academicians and thought leaders have agreed that these new network systems would employ highly exciting, developed technologies like SDN and NFV to realize their objectives. The transmission speed of 5G is a lot greater than that of the present network Data transmission speeds up to 10Gbps, which are 10 to 100 times faster than 4G and 4G- LTE will be available with 5G. To facilitate the development of new services, 5G is anticipated to merge ultra-broadband networks and incorporate new-age technologies like the Internet of Things (IoT), blockchain, big data, artificial intelligence, machine learning and cloud computing. © 2023 IEEE.

关键词： 5G mobile communication systems

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NeuroDAVIS-FS: Feature Selection Through Visualization Using NeuroDAVIS 27th

NeuroDAVIS-FS: Feature Selection Through Visualization Using...

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27th international conference on pattern recognition, ICPR 2024

作者： Maitra, Chayan Sengupta, Anwesha De, Rajat K. Machine Intelligence Unit Indian Statistical Institute Kolkata India Department of Applied Statistics Maulana Abul Kalam Azad University of Technology West Bengal Haringhata India

ISBN: (纸本)9783031783944

Dealing with high-dimensional datasets is challenging nowadays due to computational complexity, the curse of dimensionality, and model overfitting. It becomes necessary to reduce the dimension of the dataset for a better understanding of inherent information. Feature selection techniques are widely utilized to rank features based on their importance and accordingly reduce the dimension of the original datasets with respect to this ranking. Existing feature selection methods are mainly developed for specific downstream tasks and show several drawbacks e.g., not considering the inherent associations and their importance. In most of the cases, the methods are computationally expensive as well. In order to address such drawbacks, the present study aims to propose a feature selection method, called NeuroDAVIS-FS, which performs in an unsupervised learning setup without assuming any prior data distribution. Initially, it considers training using the model NeuroDAVIS, developed earlier for data visualization, and selects features according to the trained model. The efficacy of the proposed NeuroDAVIS-FS has been demonstrated on various datasets from different domains and found to be effective in comparison with state-of-the-art feature selection methods. In addition, two case studies on image and biological datasets with a very low sample-feature ratio, have been executed and found to be effective for relevant feature selection. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Feature Selection

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RSVT 2022 - 2022 3rd international conference on Robotics Systems and Vehicle Technology

RSVT 2022 - 2022 3rd International Conference on Robotics Sy...

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3rd international conference on Robotics Systems and Vehicle Technology, RSVT 2022

ISBN: (纸本)9781450396783

The proceedings contain 13 papers. The topics discussed include: obstacle-recognition method for soccer robot based on human selective attention;development of an underwater cleaning robot with vortex suction mechanism;development of an underwater cleaning robot with vortex suction mechanism;analyzing the influence of driver, route and vehicle-related factors in electric vehicle energy consumption, based on real life data;abuse torque load simulation and design of differential mechanism in hybrid electric vehicle;estimation of maximum friction coefficient using recurrent artificial neural networks;design of intelligent protection device based on numerical control tool;research on working condition transformation of Huangshan test bench based on Markov braking vibration noise;machinery fault diagnosis using continuous wavelet transform and artificial intelligence based classification;and numerical study of the axial mechanical properties of braided corrugated hose with different braiding angles.

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Sensitive Data Classification of Imbalanced Short Text Based on Probability Distribution BERT in Electric power industry

Sensitive Data Classification of Imbalanced Short Text Based...

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2023 international conference on pattern recognition, machine Vision and Intelligent Algorithms, PRMVIA 2023

作者： Zhang, Wensi Liang, Xiao Zhang, Yifang Su, Hanchen State Grid Smart Grid Research Institute Co.Ltd. Artificial Intelligence on Electric Power System State Grid Corporation Joint Laboratory Beijing China

ISBN: (纸本)9798350346596

The exploitation of big data in industrial fields faces several challenges, such as data privacy and security, data integration and interoperability, and data analysis and visualization. Data privacy and security is a major concern, as the data collected from industrial fields often contain sensitive information. Due to the particularity of the industrial field, there are challenges in the utilization of big data. 1. The distribution of different categories data is extremely uneven;2. There are a large number of industry terms in the short texts that constitute the metadata, which makes semantic representation difficult. These two challenges have a large impact on the application performance of existing models. In order to resolve the problems above, this paper proposes a pre-training model based on probability distribution, which for the classification of sensitive data in the power industry. The model consists of three modules: 1. The data enhancement module adopts the technology of synonym expansion and noise introduction, so that the model can extract the classification features of sensitive data with a small proportion;2. The pre-training module adopts the BERT model, which can obtain the semantics of industry terms in short texts;3. The probability prediction module is used to regularize the distribution of test data to meet the training data. Compared with the traditional classification model and the classification model based on deep learning, the F1-score can be improved by 36.68% and 6.39%. © 2023 IEEE.

关键词： Probability distributions

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Action recognition System Based 5G Communication and Edge Computing for Service Robot

Action Recognition System Based 5G Communication and Edge Co...

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Computer Communication and Artificial intelligence (CCAI), international conference on

作者： Yanming Zhang Cailun Wei Gangcan Sun Dawei Zhang School of Electrical and Information Engineering Zhengzhou University Zhengzhou China School of Computer and Artificial Intelligence Zhengzhou University Zhengzhou Zhengzhou

Action recognition is one of the most critical technologies for the robot to provide service excellently. In order to solve the problems of low accuracy, limited arithmetic power, and low intelligence of service robot's action recognition, an action recognition system based on 5G communication and edge computing is proposed. Communication and data interaction between robot and edge computing device is realized by using 5G routers and technologies such as NAT and Socket. A LightSlowfast network is designed for the service robot, which improves action recognition accuracy while reducing the computational effort. The experimental results show that the Light-Slowfast network achieves 72.9% accuracy on the HMDB51 dataset. The system performs well in practical tests, and the low latency of data transmission can satisfy the robot's demand for real-time action recognition.

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Research on Network Security Threat Detection and Response Mechanism Based on Artificial intelligence 25

Research on Network Security Threat Detection and Response M...

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Proceedings of the 2025 3rd international conference on Communication Networks and machine Learning

作者： Fan Zhao Key Laboratory of Science and Technology Evaluation and Monitoring of Gansu Institute of Science and Technology Information of Gansu Lanzhou Gansu China

ISBN: (纸本)9798400713231

With the rapid development of information technology, network security threats are becoming increasingly serious. Traditional network security defense mechanisms face many challenges and urgently need new solutions. The rapid development of artificial intelligence (AI) technology provides new solutions and methods for network security. This paper studies this issue and proposes a network security threat detection and response mechanism system based on artificial intelligence. First, the network security threat detection and response mechanism system based on artificial intelligence is introduced, and the convolutional neural network training model is determined. Secondly, the overall architecture process of the system is introduced. Finally, the NSL-KDD dataset is combined for verification. The results show that the proposed system has high recognition accuracy and recall rate under four types of network security attacks, verifying the effectiveness of the proposed system.

关键词： Artificial intelligence

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Framework for the Deployment of Intelligent Smart Cities (ISC) using Artificial intelligence and Software Networking Technologies 3

Framework for the Deployment of Intelligent Smart Cities (IS...

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3rd international conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2023

作者： Mohamed, Nachaat Upadhyay, Ramakant Jakka, Geethamanikanta Rambabu, P.V. Alfurhood, Badria Sulaiman Singh, Devesh Pratap Universiti Sains Malaysia Rabdan Academy UAE Homeland Security Abu Dhabi United Arab Emirates Sanskriti University Department of CSE Mathura Uttar Pradesh India University of the Cumberlands Data Analytics Information Technology United States Civil Engineering Princess Nourah Bint Abdulrahman University College of Computer and Information Sciences Department of Computer Sciences Saudi Arabia

ISBN: (纸本)9798350399264

This article's goals include providing a framework for interpersonal and communication to safeguard welfare services and assess how well the innovation ecosystem is now understood. An essay starts with an overview or description of "urban area"This viewpoint includes neighborhood services, modern amenities, or smart infrastructure. Information and technology, digital operations use, monitoring, and interconnection, amongst other things. The section that follows examines various urban planning concerns, either administration or expansion. Utilizing diverse technologies effectively is made possible by innovative information about towns or an answer to a question concerning high-quality public infrastructure. An innovative method of managing networks is the Software Defined Network (SDN) architecture. Unlike switches in a conventional network computing environment, changes in SDN do not process inbound sachets in the similar means. If no inbound packets are identified after searching the linking tables, they are passed to the control system, the SDN's operating system, for processing. A Spread Denial of Service (DoS) outbreak poses the biggest risk to the cyber security of an SDN *** system or application layers of the disease-ridden devices connected to the system will be the target of the attack. The approach for determining whether incoming packets are contaminated or not is clever machine learning-based, and it is proposed in this paper. In the context of smart cities, the deployment of artificial intelligence (AI) has newly drawn more and more attention. The purpose of this study is to perform a works assessment to examine the role of AI in the various parts of smart towns given the relevance of the topic. This study's technique combines a thorough literature evaluation to find the most pertinent papers with reference system investigation to reveal the subtleties of the subject. The findings of this study highlight the significance of this technology, whic

关键词： Smart city

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